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The Non-Technical Guide to Machine Learning & Artificial Intelligence

I have a challenge for you.

In a few seconds, I want you to stop reading this article, and follow the instructions below.

Here you go:

1. Visit your your favorite source for Tech news (Twitter, Hacker News, Term Sheet, reddit, TechCrunch, Mattermark Daily, CB Insights, etc.)2. Hit “crtl + f”3. Search “artificial intelligence” or “machine learning”4. If you don't find any matches, publicly shame me on Twitter.

I hope my point is obvious.

Machine learning and artificial intelligence (ML and AI) have seized Tech mindshare in a way few topics have in recent memory. A couple months ago I noticed people talking about artificial intelligence everywhere I looked. According to AI experts, everything from our jobs, to the wars we wage, to the food we eat, to the beer we drink, to the software we write will be affected.

Not being one to enjoy surprises, I decided to spend my free time learning as much about the space (and what the future holds) as possible. ML and AI are having a huge impact on our lives, and their roles are only increasing. The better informed you are, the better prepared you’ll be to handle these changes as they happen.

Rather than sit here and pretend I know everything there is to know about ML and AI, I’m going to hand you the resources I use to educate myself.

I hope you will use them too.

Join 30,000+ people who read the weekly 🤖Machine Learnings🤖 newsletter to understand how AI will impact the way we work and live.

How to Use This List

There is already a ton of technical content being produced about artificial intelligence and machine learning. This list is a primer for non-technical people who want to understand what machine learning makes possible.

To develop a deep understanding of the space, reading won’t be enough. You need to: have an understanding of the entire landscape, spot and use ML-enabled products in your daily life (Spotify recommendations), discuss artificial intelligence more regularly, and make friends with people who know more than you do about AI and ML


Startups: I’ve included links to the websites and apps of 307+ machine intelligence companies and tools.

Alongside Mark Philpot, Avi Eisenberger, and Samiur Rahman, I’m building Journal — a product that uses machine learning to help people remember all the information they’ve come across that will be useful in the future.

News: For starters, I’ve included a link to a weekly artificial intelligence email that Avi Eisenberger and I curate (🤖Subscribe to Machine Learnings🤖). Start here if you want to develop a better understanding of the space, but don’t have the time to actively hunt for machine learning and artificial intelligence news.

People: Here’s a good place to jump into the conversation. I’ve provided links to Twitter accounts (and LinkedIn profiles and personal websites in their absence) of the founders, investors, writers, operators and researchers who work in and around the machine learning space.

Events: If you enjoy getting out from behind your computer, and want to meet awesome people who are interested in artificial intelligence in real life, there is one place that’s best to do that, more on my favorite place below.

  • LinkedIn
  • Facebook

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